A molecular spectrometer (sometimes referred to as a spectroscope) is an instrument wherein a solid, liquid, or gaseous sample is illuminated, often with non-visible light such as light in the infrared region of the spectrum. The light from the sample is then captured and analyzed to reveal information about the characteristics of the sample. As an example, a sample may be illuminated with infrared light having known intensity across a range of wavelengths, and the light transmitted and/or reflected by the sample can then be captured for comparison to the illuminating light. Review of the captured spectra can then illustrate the wavelengths at which the illuminating light was absorbed by the sample. To illustrate, FIG. 1 illustrates an exemplary spectrum (denoted U) presented as a plot of light intensity versus light wavelength. The spectrum, and in particular the locations and amplitudes of the “peaks” therein, can be compared to libraries of previously-obtained reference spectra (denoted as L1, L2, . . . LN) to obtain information about the sample, such as its composition and characteristics. In essence, the spectrum serves as a “fingerprint” for the sample and for the substances therein, and by matching the fingerprint to one or more known fingerprints, the identity of the sample might be determined.
However, as when identifying a fingerprint, it can prove difficult and time-consuming to find a match for an unknown spectrum in a reference library. Even where an unknown spectrum is obtained from a sample having the same composition as the one from which a reference spectra was captured, an exact match is unlikely owing to differences in the measurement conditions between the unknown and reference spectra (e.g., differences in intensity/amplitude, differences in wavelength scaling/binning, different background noise levels, etc.). Further, while reference spectra are usually obtained from pure substances, unknown spectra often aren't. The unknown spectrum will therefore not match a single one of the reference spectra L1, L2, . . . LN, and will rather match a combination of two or more of these spectra. In such a combination, the spectra are effectively “overlaid” with each other, though each may have a different weight depending on the relative concentrations of the substances from which they originate. It should be appreciated that if one wishes to compare an unknown spectrum U to all possible combinations of one or more reference spectra L1, L2, . . . LN, this will typically be an exceedingly large number, particularly where a large reference library may have tens of thousands of entries (N being equal to the number of these entries). The computational time needed to perform these comparisons can be further magnified if quantitative analysis is to be performed as well as qualitative analysis, i.e., where the relative proportions of component spectra within the unknown spectrum are to be determined as well as their identities. Such quantitative analysis may require that regression be performed between a combination of reference spectra versus the unknown spectrum to determine the weighting that each reference spectrum should have to result in a combination which best matches the reference spectrum. As a result, exhaustive spectral matching can sometimes take hours—or even days—to perform, even where dedicated computers or other machines with high-speed processors are used.